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#import cv2
#import numpy as np
import gradio as gr
inputs_image = gr.Image(type="filepath", label="Input Image")
# def img_inf(img, model):
# model, classes, colors = load_model() # Load the MobileNet-SSD model
# image, height, width, channels = load_img(img) # Load and preprocess the image
# blob, outputs = detect_objects(image, model) # Detect objects in the image
# boxes, class_ids = get_box_dimensions(outputs, height, width) # Get the bounding boxes
# return cv2.cvtColor(image1, cv2.COLOR_BGR2RGB) # Re
def ff(ev):
print(ev)
interface_image = gr.Interface(
fn=ff,
inputs=[inputs_image],
#outputs=outputs_image,
title="Image Inference",
description="Upload your photo and select one model and see the results!",
# examples=[["sample/dog.jpg"]],
cache_examples=False,
) |